Merge JSON Data: Boost Sync & Reduce File Count

Hey everyone! Today, we're diving into a really neat optimization we can make within our surface folders that's going to significantly improve our sync performance. We're talking about merging the data from overlapping.json files into our meta.json files. This might sound a bit technical, but trust me, the payoff is huge, especially when you're dealing with a ton of small surfaces.

The Current Situation: meta.json and overlapping.json

Currently, in our surface folders, we have two primary JSON files: meta.json and overlapping.json. The meta.json file, as the name suggests, contains crucial metadata about the surface. This could include things like the surface's dimensions, creation date, modification history, and other essential descriptive information. Think of it as the surface's identity card, holding all the key details.

On the other hand, overlapping.json specifically stores data related to overlaps between surfaces. This is particularly important in scenarios where surfaces might be adjacent or share common boundaries. This file helps us understand the spatial relationships between different surfaces, which is vital for a variety of applications, such as volume cartography and ScrollPrize projects. Imagine you're piecing together a giant jigsaw puzzle; the overlapping.json tells you which pieces fit next to each other.

Having these two files separate has served its purpose, but as we scale up our operations and handle more and more small surfaces, the sheer number of files we're tracking starts to become a bottleneck. This is where the idea of merging comes into play.

Why Merge? The Benefits of Consolidation

The main driver behind this merge is to reduce the overall number of files we're tracking. When you're dealing with a massive number of small surfaces, having separate meta.json and overlapping.json files for each surface quickly adds up. We're talking potentially tens of thousands of files! Each file adds overhead in terms of storage, indexing, and, most importantly, sync performance.

Think about it: every time you sync your files, your system needs to check the status of each individual file. The more files there are, the longer this process takes. By merging the contents of overlapping.json into meta.json, we effectively halve the number of files that need to be tracked. This directly translates to faster sync times and a more responsive system. Imagine the difference between having to check 10,000 items versus 20,000 – that's a significant speed boost!

Streamlined File Management

Beyond sync performance, merging these files also simplifies our file management. It's just easier to deal with one file per surface than two. This reduces clutter, makes it simpler to locate the information you need, and minimizes the chances of accidentally misplacing or overlooking a file. Less clutter, more clarity – that's always a win!

Improved Data Cohesion

Consolidating the metadata and overlapping data into a single file also promotes better data cohesion. All the relevant information about a surface is now in one place, making it easier to access and process. This can be particularly beneficial for applications that need to access both types of information simultaneously. Instead of having to open and read two separate files, they can get everything they need from a single source.

How We'll Merge the Data: A Practical Approach

So, how do we actually go about merging these files? The process is relatively straightforward, but it's important to follow the steps carefully to avoid any data loss or corruption.

1. Read the Contents: First, we need to read the contents of both the meta.json and overlapping.json files for a given surface. This involves opening the files and parsing the JSON data into a usable format, such as a dictionary or object in your programming language of choice.
2. Merge the Data: Next, we'll merge the data from overlapping.json into meta.json. This typically involves adding a new section or key within the meta.json structure to house the overlapping data. For example, you might create a new field called `